Leistungsanalyse von Algorithmen zur Auswertung von Assoziationsregeln

Association rule mining techniques are an important part of data mining, used to derive relationships between attributes in large databases. Association rule mining has garnered significant interest from researchers, as it can solve many complex problems. Numerous algorithms have been developed to effectively derive association rules. It has been found that not all algorithms can produce similar results in every scenario, making it essential to decipher these advantages. In this context, association rule mining algorithms have been analyzed, and a comparative study of these algorithms has been experimentally conducted using various datasets and parameters.